3 papers
cs.CY2026
Personalized Recommendations Without Inducing Congestion: Mitigating Disparities in the NYC High School Match
Erica Chiang, Kenny Peng, Rebecca Lichtenstein +7
Algorithmic recommendations can help participants navigate large matching markets. For example, recommendations for school and college choices may reduce information frictions and…
cs.LG2025
Reflections from Research Roundtables at the Conference on Health, Inference, and Learning (CHIL) 2025
Emily Alsentzer, Marie-Laure Charpignon, Bill Chen +90
The 6th Annual Conference on Health, Inference, and Learning (CHIL 2025), hosted by the Association for Health Learning and Inference (AHLI), was held in person on June 25-27, 2025…
cs.LG2024
Learning Disease Progression Models That Capture Health Disparities
Erica Chiang, Divya Shanmugam, Ashley N. Beecy +4
Disease progression models are widely used to inform the diagnosis and treatment of many progressive diseases. However, a significant limitation of existing models is that they do…